The Principal Component Analysis (PCA) is one of the most successful techniques that have been used in image recognition and compression. PCA is a statistical method under the broad title of factor analysis. The purpose of PCA is to reduce the large dimensionality of the data space (observed variables) to the smaller intrinsic dimensionality of feature space (independent variables), which are n...

Segmentation of Grey/White/CSF from MR images depends on contrast to noise ratios (CNR) among these tissues and the CSF. The CNRs are determined by the acquisition method and imaging parameters. These factors can be optimized for improved image segmentation [1,21. In many MR studies, multiple images of the same slice locations are acquired, each with different weightings based Tl/T2/proton dens...

For improving accuracy and increasing efficiency of classifier, there are available many effective techniques. One of them combining multiple classifier technique is used for this purpose. In this paper I present a novel approach to a combining algorithm designed to improve the accuracy of principle component classifier. This novel approach combines multiple PCA classifiers, each of using a sub...

Although many modern imaging systems are still producing grayscale images, colored-images are more preferred for the larger amount of information they are carrying. Computing the grayscale representation of a color image is a straightforward task, while the inverse problem has no objective solution. The search through out literature has not revealed much history of the past works. In this paper...

In the beginning stage, face verification is done using easy method of geometric algorithm models, but the verification route has now developed into a scientific progress of complicated geometric representation and matching process. In modern time the skill have enhanced face detection system into the vigorous focal point. Researcher’s currently undergoing strong research on finding face recogn...

We present a method for analyzing and resynthesizing inhomogeneously textured regions in images for the purpose of advanced compression. We first define image blocks in a way that they cover regions with homogenious texture. These blocks are transformed each in turn. For the transform we use the so called Principle Component Analysis. After the transform into the new domain we statistically ana...